Introduction

This data has been pulled from Seattle Open Data. I chose to observe the changes in checkout materials over the course of the last 5-6 years, the most popular publishers, the average checkouts each title has, and the publication year that has accumulated the most checkouts. For the checkout material trends, I was very curious to see how the numbers changed before, during, and after COVID. I was interested in learning which publishers are the most popular based on the checkouts because I realized I didn’t know many other publishers beside Penguin. The average checkouts and publication year with the most checkouts was something I didn’t have a hypothesis going into so I wanted to learn a bit more about this aspect. An introduction of the data and a description of the trends/books/items you are choosing to analyze (and why!) -Trends of physical and ebook checkouts over time -Average number of checkouts per item - -Publication year with the most checkouts. -Top 5 most popular subjects

Summary Information

Write a summary paragraph of findings that includes the 5 values calculated from your summary information R script

These will likely be calculated using your DPLYR skills, answering questions such as:

Feel free to calculate and report values that you find relevant.

The Dataset

Your Choice

The last chart is up to you. It could be a line plot, scatter plot, histogram, bar plot, stacked bar plot, and more. Here are some requirements to help guide your design:

Here’s an example of how to run an R script inside an RMarkdown file: